1. Technical Field
The invention relates generally to measurement systems, and more particularly, to methods, system and program product for optimizing a measurement system under test (MSUT).
2. Background Art
Measurement systems (i.e., metrology tool(s)) are used to measure many structures during various process steps in the semiconductor fabrication industry. The measurements may include, for example, gate critical dimensions on a critical dimension scanning electron microscope (CD-SEM) or scatterometry tool, gate dielectric thickness on thin film measuring tools, the overlay between gate level and first level print and via measurement in the back end of line (BEOL). The measurements are used to control processing at levels based on the International Technology Roadmap for Semiconductors (ITRS).
One challenge for obtaining quality measurements is managing the hundred or more decisions being made as measurement recipes for measuring a process step are constructed, each of which may lead to a difference in measurement. In particular, each person operating a measurement system may use different values for adjustable parameters of a measurement system that determine how well the measurement system will measure a given target, e.g., wafer and process step, being measured. Determining which values of adjustable parameters results in an optimized measurement, e.g., best precision, best accuracy, best matching, etc., is very difficult to accomplish.
Conventionally, the optimization process is performed using the simplest metric, precision. Unfortunately, using only the precision can lead to missing key issues in the optimization selection process. For example, if a smoothing filter on a CD-SEM algorithm at gate etch critical dimension measurement is changed and the response to precision is observed, one would find that generally the higher the smoothing the better the precision thereby suggesting that higher smoothing equates to better quality measurements. But, if one used a different quality metric, for example, accuracy, then one would come to a different conclusion. It turns out that there exists a balancing point between precision and accuracy, the higher smoothing filter sizes end up smoothing too much at the expense of accuracy in the measurement. The above-described problem is magnified because the measurement of each of the hundreds of the monitored process steps in a manufacturing setting requires its own custom optimization.
If optimized correctly, the resulting measurements provide better process control discrimination, and better correlation to electrical test parameters. Unfortunately, for many process steps, a measurement system error (e.g., precision, matching and/or accuracy) is high with respect to the tolerances at which the process step must be controlled. This is traditionally referred to as a precision to tolerance (P/T) ratio. In this case, a measurement system error as determined based on a quality metric should consume no more than, for example, 20% of the tolerance. A quality metric may include measures such as single tool precision, fleet matching precision (FMP), total measurement uncertainty (TMU) (also referred to as accuracy) or a combination thereof. The closer the P/T ratio is to unity, the less likely it is that the process can be controlled to the required tolerances because the measurement uncertainty is too high, making it difficult to de-couple process variation from measurement error. Accordingly, a solution to optimize a measurement system is needed.